The present invention relates to a scanning type charged particle beam microscope that radiates charged particles against a sample to obtain its image and an image processing method using this microscope. More specifically, the present invention relates to a method and a device that perform an image quality improvement operation on the obtained image.
For a clear observation of minute structures of an object being examined, scanning type charged particle beam microscopes with a higher resolution than that of optical microscopes are widely in use. The charged particle beam microscope irradiates a sample under inspection with a charged particle beam and detects charged particles released from the sample or those that have passed through it (charged particles of the same or different species than that of the irradiated charged particles, or electromagnetic waves) to produce an enlarged image of the sample being inspected.
In a semiconductor manufacturing process, scanning type charged particle beam microscopes such as a scanning electron microscope (SEM), a scanning ion microscope (SIM) and a scanning transmission electron microscope are used for such applications as semiconductor wafer inspection and pattern measurement. In these applications, images that are shot are used for observation of semiconductor patterns and defects, for defect detection and analysis of causes and for measurement of pattern dimensions.
In the scanning type charged particle beam microscope, the function of providing high quality images is one of its most important functions. Although improvements of hardware such as a charged-particle-beam optical system and a detection system can allow for enhanced resolution and S/N of images to a certain degree, there is a limit. As to the resolution, diffraction aberrations caused by charged particles having a nature of waves and chromatic and spherical aberrations due to characteristics of charged particle lens will inevitably result in a degradation of the resolution. As for the S/N, it can be enhanced by increasing the amount of charged particle beam to be radiated. This method, however, has a problem of causing damages to a sample or prolonging the imaging time. In practice therefore, the amount of charged particle beam that can be applied is limited, resulting sometimes in a failure to secure a sufficient S/N.
Other than the method of improving hardware, a method is available that enhances the resolution and the S/N by performing an image quality improving operation on the sample image. As methods for improving the resolution and S/N, an edge emphasizing operation, an image restoration operation and a noise removing operation are proposed in JP-A-63-211472 and JP-A-3-44613. Among other image quality improving operations there is proposed a technique that performs a contrast correction operation on the sample image to adjust brightness and contrast appropriately and thereby enhance the quality of the output image (e.g., Y. I. Gold and A. Goldenshtein: Proc. SPIE, 3332, pp. 620-624 (1998)).
JP-A-2002-328015 describes a method that uses a matching operation to align positions of two images.
In the methods proposed by JP-A-63-211472 and JP-A-3-44613 and by Y. I. Gold and A. Goldenshtein: Proc. SPIE, 3332, pp. 620-624 (1998), the image quality improvement operation is done by using only a sample image or by using the sample image and imaging or shooting conditions (an acceleration voltage of charged particle beam, a probe current, etc.). The above methods, however, do not perform an operation using design data or an operation using design data and sample characteristic information. Here, the design data refers to data representing information on geometries of semiconductor patterns to be manufactured, and in many cases describes the geometries of semiconductor patterns as by information on their outlines.
Therefore, with the conventional operations, a sufficient image quality improvement may not be obtained as described below.
The use of only the sample image and the imaging conditions cannot produce sample characteristic information for each area on the image. Nor can it decide whether spatially separate areas on the image have similar sample characteristics (material characteristics, electrical characteristics, layer characteristics, etc.). Therefore, it is not possible to perform an appropriate image quality improvement operation according to the sample characteristics of each area, make sample characteristic differences visible or emphasize only a sample having a particular characteristic
In the conventional method, to perform operations, such as emphasizing a contrast between different areas and optimizing process parameters for each area, requires dividing the area of the image. However, the area division takes a long duration of processing and it is difficult to meet both requirements for a high precision of area division and a reduced processing time simultaneously.
The area on a sample that the user particularly wishes to observe is often the one where the difference between actual data and design data is large. The image quality improvement operation that automatically emphasizes such an area is difficult to perform with the conventional method.